Introduction to machine learning in Python with scikit-learn (video series)

In the data science course that I teach for General Assembly, we spend a lot of time using scikit-learn, Python's library for machine learning. I love teaching scikit-learn, but it has a steep learning curve, and my feeling is that there are not many scikit-learn resources that are targeted towards machine learning beginners. Thus I decided to create a series of scikit-learn video tutorials, which I launched in April in partnership with Kaggle, the leading online platform for competitive data science!

The series now contains nine video tutorials totaling four hours. My goal with this series is to help motivated individuals to gain a thorough grasp of both machine learning fundamentals and the scikit-learn workflow. I don't presume any familiarity with machine learning, which is why the first video focuses exclusively on answering the question, "What is machine learning, and how does it work?" And although the series does assume that you have some familiarity with Python, the second video contains my suggested resources for learning Python if you're just getting started with the language.

I've embedded the video playlist below, or you can watch it on YouTube. I've also listed the agenda for each video, along with links to the blog post and Jupyter Notebook associated with each video. (My GitHub repository contains all of the Notebooks, which may be useful as reference material!)